Anthony K. H. Tung (鄧锦浩),Assistant Professor,School of Computing,National University of Singapore,Singapore
Cuiping Li (李翠平),Associate Professor,School of Information,Renmin University of China,ChinaCourse Description
This course will introduce various data mining techniques, the foundation on which they are developed and their emerging applications in domains like bioinformatics and multimedia processing. At the end of the course, students can expect to gain enough understanding of data mining to effectively do research in the area. Topics that will be covered in the course includes but is not limited to:
- basic spatial, string indexing techniques etc.- basic data summarization techniques like histograms, data cubes etc.- basic data mining techniques like association rules mining, classifier induction and clustering analysis etc.- advanced data mining operators like similarity search functions, skyline computation and dominant relationship analysis- advanced data mining techniques on high dimensional data and complex structures like sequences, trees and graphsAudiences
Graduate students or senior undergraduates who are interested to do research in data mining.Textbooks and Papers
．Principles of Data Mining, David Hand, Heikki Mannila and Padhraic Smyth, The MIT Press, 2001.
．J. Han and M. Kamber, Data Mining: Concepts and Techniques, Second Edition, Morgan Kaufmann, 2006
．Machine Learning, Tom M. Mitchell, McGrawHill, 1997.
A set of research papers selected by the lectures to be given out later.Date
4th to 10th of December 20072 lessons per day with optional lessons on techniques of doing research in some of the nights.Charge
The course is free. The audiences need to afford all other fees (such as accommodation, traffic) by themselves.Location
Lecture Hall, Key Lab of Data and Knowledge Engineering, Renmin University of China, Beijing, ChinaApplication
Send application either to firstname.lastname@example.org or email@example.com by 1st October 2007